2 research outputs found
Validating a bike network analysis score based on open data as a connectivity measure of urban cycling infrastructure adapted for European Cities
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesCycling has been considered a viable option to generate a modal shift from fossil
dependent transportation modes. In this framework, measurements and tools that
aid connected bicycle infrastructure planning have been developed. This is the case
of the Bicycle Network Analysis score, a connectivity measure adapted for the U.S.
It is based on the Levels of Traffic Stress methodology and computed mainly with
OpenStreetMap data. Its aim is to quantify how well the low-stress bicycle network
in a city connects people with the places they want to go. For this research, the
BNA open source tool is adapted to a European context to validate its ability of
quantifying low-stress connectivity. Three core elements are evaluated: stress network,
destinations, and the overall score itself. They are related to cycling behaviors
from two validation data sources: travel to work data in England and Wales, and
crowdsourced bicycle trip routes in The Netherlands. The results indicate that
in England and Wales, there is a significantly higher percentage of bicycle trips
performed between origin-destination pairs with a low-stress connection between
them. Additionally, a positive correlation is found between the percentage of bicycle
trips within a city and its overall BNA score. In the Dutch case, the destinations core
element is evaluated, determining that the destinations contemplated in the BNA
score calculation are also among the highly frequented by cyclists. However, their
importance within the score computation might require adjustments. Although a
comprehensive validation cannot be achieved due to data limitations, evidence that
providing low-stress connections between origins and destinations relates to bicycle
commuting in cities is found. Therefore, special attention should be given to those
measures that can greatly benefit the decision-making process when planning for
sustainable cities